English(EN) Learning Subgroup Relations Using Siamese Graph Neural Networks

Siamese GNN 以 95.9% 的准确率预测有限群的子群关系

作者 PulseAugur 编辑部 · [2 个来源] · 2026-07-13 06:20

研究人员开发了一种 Siamese 图神经网络 (Siamese GNN) 来预测有限群中的子群关系。该模型使用 Cayley 图表示群，并生成与代数特征相结合的嵌入。该方法在独立测试集上达到了 95.9% 的准确率，展示了几何深度学习在计算群论问题中的潜力。 AI

影响这项研究展示了几何深度学习在解决计算群论复杂问题方面的新颖应用。

排序理由该集群包含一篇详细介绍新型机器学习模型及其实验结果的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.LG TIER_1 English(EN) · Tal Weissblat · 2026-07-14 04:00

使用 Siamese Graph Neural Networks 学习子群关系

arXiv:2607.11140v1 Announce Type: new Abstract: Determining whether one finite group is isomorphic to a subgroup of another is a fundamental problem in computational group theory. In this work, we propose a Siamese Graph Neural Network (Siamese GNN) for subgroup prediction using …
arXiv cs.LG TIER_1 English(EN) · Tal Weissblat · 2026-07-13 06:20

使用 Siamese Graph Neural Networks 学习子群关系

Determining whether one finite group is isomorphic to a subgroup of another is a fundamental problem in computational group theory. In this work, we propose a Siamese Graph Neural Network (Siamese GNN) for subgroup prediction using Cayley graph representations of finite groups. E…